[4E3-GS-8] Robot and real worlds:

[4E3-GS-8-01] Acceptance Probability Analysis in Joint-Attention Naming Game Including the Turing Test

〇Yusuke Sasai¹, Ryota Okumura¹, Takafumi Horie¹, Yoshinobu Hagiwara¹, Akira Taniguchi¹, Tadahiro Taniguchi¹ (1. Ritsumeikan University)

Keywords:Symbol Emergence in Robotics, Experimental Semiotics, Human-Robot Interactions

Humans adjust their attitudes according to their communication partners. The Metropolis-Hastings Naming Game (MHNG) is a theory that mathematically represents the likelihood of accepting others' opinions based on Bayesian inference as acceptance probability. Previous research demonstrated MHNG's effectiveness in explaining human acceptance probabilities through experiments with the Joint-attention naming game (JA-NG), which removed acceptance probability constraints from MHNG. It also suggested biases in human acceptance probabilities towards easier acceptance. This research investigated how the perception of the counterpart agent influences biases by conducting JA-NG experiments, including the Turing Test, and analyzing biases based on whether the counterpart was perceived as human or computer. No significant differences were found in biases in acceptance probabilities between perceiving the counterpart as human or computer. Furthermore, MHNG, proposed as a model for symbol emergence in human communication, tended to be less likely to be evaluated as human than other computer models.